Intensity-modulated radiation therapy: a review with a physics perspective

A machine learning toolkit assisted approach for IMRT fluence map optimization: feasibility and advantages

Purpose. Traditional machine learning (ML) and deep learning (DL) applications in treatment planning rely on complex model architectures and large, high-quality training datasets. However, they cannot fully replace the conventional optimization process. This study presents a novel application of ML in treatment planning where established ML/DL toolkits are directly applied to treatment plan optimization.Materials and Methods. A one-layer network was designed based on the dose deposition matrix and implemented in PyTorch's L-BFGS optimizer with GPU acceleration. The classical steepest descent optimizer was selected as a reference for comparison. Both optimizers utilized identical inputs and objective functions to ensure a fair comparison. DVH- and gEUD-based objectives were implemented in standard quadratic forms. Standard uniform and 1,000 random initializations were used to test optimizer's search ability under different starting conditions for prostate and head-and-neck cases.Results. The MLT-assisted framework demonstrated comparable or superior plan quality to classical optimization by achieving lower objective values, improved DVHs and capturing finer modulation details in fluence maps. For gEUD-based optimization, it effectively explored beam weight elevations that classical optimization could only reach with stricter convergence criteria and many more iterations. The quality differences primarily stemmed from convergence speed. The MLT-assisted framework required significantly fewer evaluations and iterations to achieve similar or better results. Optimization on random initial maps further demonstrated that it was more robust and less likely to be trapped. It does not require stricter convergence criteria or extended runs to reach high-quality optima, making it more efficient and reliable.Conclusion. This framework leverages ML toolkits in a novel way, enabling faster convergence, greater robustness and handling of complex constraints. As the first study of its kind, it establishes MLT-assisted optimization as a viable and effective alternative to classical methods.

Beam collimation and filtration optimization for a novel orthovoltage radiotherapy system

BACKGROUND

The inaccessibility of clinical linear accelerators in low- and middle-income countries creates a need for low-cost alternatives. Kilovoltage (kV) x-ray tubes have shown promise as a source that could meet this need. However, performing radiotherapy with a kV x-ray tube has numerous difficulties, including high skin dose, rapid dose fall-off, and low dose rates. These limitations create a need for highly effective beam collimation and filtration.

PURPOSE

To improve the treatment potential of a novel kV x-ray system by optimizing an iris collimator and beam filtration using Bayesian techniques and Monte Carlo (MC) simulations.

METHODS

The Kilovoltage Optimized AcceLerated Adaptive therapy system's current beam configuration consists of a 225 kVp x-ray tube, a 12-leaflet tungsten iris collimator, and a 0.1 mm copper filter. A Bayesian optimization was performed for the large and small focal spot sizes of the kV x-ray tube source at 220 kVp using TopasOpt, an open-source library for optimization in TOPAS. Collimator thickness, copper filter thickness, source-to-collimator distance (SCD), and source-to-surface distance (SSD) were the variables considered in the optimization. The objective function was designed to maximize the dose rate and the dose at a depth of 5 cm while minimizing the beam penumbra width and the out-of-field dose (OFD), all evaluated in a water phantom. Post-optimization, the optimal beam configuration was simulated and compared to the existing configuration.

RESULTS

The optimal collimation setup consisted of 2.5 mm thick tungsten leaflets for the iris collimator and a 350 mm SSD for both focal spot sizes. The optimal copper filtration was 0.22 mm for the large focal spot and 0.15 mm for the small focal spot, with a SCD of 148.5 mm for the large focal spot and 125.8 mm for the small focal spot. For the large focal spot, the surface dose rate decreased by 9.4%, while the PDD at 5cm depth (PDD 5 c m $\text{PDD}_{5\textnormal {cm}}$ ) increased by 7.7% compared to the existing iris collimator. Additionally, the surface beam penumbra width was reduced by 31.3%, and no significant changes in the OFD were observed. For the small focal spot, the surface dose rate for the new collimator increased by 3.7% and thePDD 5 c m $\text{PDD}_{5\textnormal {cm}}$ increased by 5.3%, with no statistically significant changes in the beam penumbra width or OFD.

CONCLUSION

The optimal beam collimation and filtration for both x-ray tube focal spot sizes of a kV radiotherapy system was determined using Bayesian optimization and MC simulations and resulted in improved dose distributions.

Evolution and Recent Radiation Therapy Advancement in Uganda: A Precedent on How to Increase Access to Quality Radiotherapy Services in Low- and Middle-Income Countries

The evolution of radiation therapy in Uganda has been a journey marked by significant milestones and persistent challenges. Since the inception of radiotherapy services in 1988-1989, there has been a concerted effort to enhance cancer treatment services. The early years were characterized by foundational developments, such as the installation of the first teletherapy units, low-dose-rate brachytherapy units, and conventional simulators, and the recognition of radiation oncologists and medical physicist professionals laid the groundwork for radiotherapy treatment modalities. With more support from the International Atomic Energy Agency, the acquisition of dosimetry equipment, treatment planning systems, and additional professional training signaled a new era in the fight against cancer. As we entered the second decade of the millennium, the Uganda Cancer Institute (UCI) witnessed a progression in sophisticated radiotherapy services, including high-dose-rate brachytherapy, initiation of intensity modulated radiation therapy (IMRT)/volumetric modulated arc therapy (VMAT), and use of artificial intelligence. These advancements improved the efficiency/precision of treatments and the time patients spent undergoing therapy. Around the second decade of radiotherapy services, about 600 new patients with cancer were annually treated compared with about 2,600 in 2023. Currently, an average of 1,440 brachytherapy insertions are done annually compared with 300 insertions for the first 20 years. Despite the technological strides, the UCI faced numerous obstacles, including limited equipment, knowledge gaps in appropriate tumor/organs at risk segmentations, treatment planning, and protocols. However, international support and collaboration efforts have led to significant improvement in the precision and effectiveness of treatments. Currently, about 51% of all patients are treated with image-guided techniques-IMRT/VMAT (42%) and three-dimensional conformal radiation treatment (10%). The Government has commenced the decentralization of radiotherapy services to other regions. This review can be a learning lesson for the more than 25 countries in Africa and other low-middle-income countries globally that do not have access to radiotherapy and/or are in the process of starting such facilities.

Impact of Reference Selection on Gamma Analysis in Patient-Specific Quality Assurance for Monte Carlo-Based Treatment Planning Systems

OBJECTIVE

Our study aimed to establish a standardized methodology for selecting "reference" and "evaluated" distributions in gamma analysis for Monte Carlo (MC) based intensity modulated treatment plans. Evaluation of importance of reference selection in MC based and non MC based treatment planning systems were analysed using a study classification.

METHODS

Three categories were utilized to analyzed gamma passing rates across using different treatment planning systems (TPS) and detectors for thirty five patients. Category 1 utilized MC-based Monaco TPS plans and a 2 dimensional(2D) I'mRTMatriXX detector. Category 2 employed non-MC-based Eclipse TPS plans, assessed with a 2D I'mRTMatriXX detector. In Category 3, MC-based Monaco TPS plans were validated using a Dolphin detector. All plans were subjected to analysis using gamma criteria, which considered a dose difference of 3% and a distance to agreement of 3mm. Additionally, another set of gamma criteria was employed, with a dose difference of 3% and a distance to agreement of 2mm. An introduced Asymmetric factors in both 2D and 3D analysis will quantify the asymmetric nature of gamma based on the choice of "reference" distribution.

RESULT

For 2D Gamma analysis, MC-based Monaco TPS and I'mRTMatriXX showed a consistent positive Zk2D trend for all patients, with significant p-values below 0.01 for both gamma passing criteria. In contrast, non-MC based Eclipse TPS exhibited varied Zk2D results, with non-significant p-values. In 3D Gamma analysis, all patients exhibited positive Zk3D values with significant p-values below 0.01 when "references" were swapped. The Pearson correlation between asymmetricity and isodose volumes was notably high at 0.99 for both gamma criteria.

CONCLUSION

Our study highlights the imperative of using MC-based TPS as the definitive "reference" in gamma analysis for patient specific quality assurance of intensity modulated radiation therapy, emphasizing that variations can mislead results, especially given gamma analysis's sensitivity to MC calculation noise.

Cancer treatments: Past, present, and future

There is a rich history of cancer treatments which provides a number of important lessons for present and future cancer therapies. We outline this history by looking in the past, reviewing the current landscape of cancer treatments, and by glancing at the potential future cancer therapies.

Markov models for clinical decision-making in radiation oncology: A systematic review

The intrinsic stochasticity of patients' response to treatment is a major consideration for clinical decision-making in radiation therapy. Markov models are powerful tools to capture this stochasticity and render effective treatment decisions. This paper provides an overview of the Markov models for clinical decision analysis in radiation oncology. A comprehensive literature search was conducted within MEDLINE using PubMed, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only studies published from 2000 to 2023 were considered. Selected publications were summarized in two categories: (i) studies that compare two (or more) fixed treatment policies using Monte Carlo simulation and (ii) studies that seek an optimal treatment policy through Markov Decision Processes (MDPs). Relevant to the scope of this study, 61 publications were selected for detailed review. The majority of these publications (n = 56) focused on comparative analysis of two or more fixed treatment policies using Monte Carlo simulation. Classifications based on cancer site, utility measures and the type of sensitivity analysis are presented. Five publications considered MDPs with the aim of computing an optimal treatment policy; a detailed statement of the analysis and results is provided for each work. As an extension of Markov model-based simulation analysis, MDP offers a flexible framework to identify an optimal treatment policy among a possibly large set of treatment policies. However, the applications of MDPs to oncological decision-making have been understudied, and the full capacity of this framework to render complex optimal treatment decisions warrants further consideration.

Evaluation of Dynamic Multi-Leaf Collimator (MLC) versus Fixed MLC for Intensity Modulated Radiotherapy (IMRT) Using the Agility 160-Leaf Collimator

AIM

This study aimed to evaluate the efficacy of static or step-and-shoot intensity-modulated radiotherapy (ssIMRT) and dynamic intensity-modulated radiotherapy (dIMRT) delivery techniques for various treatment sites.

MATERIALS AND METHODS

The treatment planning system (TPS) was utilized to develop optimal treatment plans for twenty-seven patients selected for this comparative study, including nine with head and neck cancer, nine with prostate cancer, and nine with cervical cancer. The prescribed doses were 7000cGy/33fr, 7425cGy/33fr, and 5000cGy/25fr for the nasopharynx, prostate, and cervix cases, respectively, in both ssIMRT and dIMRT delivery techniques. Plans were generated using the Monaco treatment planning system with a 6MV photon beam and nine equidistant fields. Plan evaluation criteria included dose-volume histogram analysis, dose homogeneity index, conformity index, radiation delivery time, and monitor unit requirements.

RESULTS

All plans were optimized to ensure that 98% of the planning target volume (PTV) received at least 95% of the prescribed dose, while meeting the planning objectives for organs at risk. dIMRT plans exhibited superior conformity (CI = 0.85 ± 0.05) compared to ssIMRT plans (CI = 0.79 ± 0.08), with statistically significant differences (P < 0.01). Inhomogeneity within the PTV was significantly higher in ssIMRT plans (HI = 0.10 ± 0.02) compared to dIMRT plans (HI = 0.09 ± 0.01), with a significant difference (P < 0.01). Delivery time per fraction was significantly lower in dIMRT compared to ssIMRT (P < 0.01). Furthermore, dIMRT plans required a higher mean monitor unit value (1335.4 ± 172.2) compared to ssIMRT plans (974.4 ± 133.6) with a significant difference (P < 0.001).

CONCLUSION

The findings of this study indicate that dIMRT provides improved target coverage, homogeneity, and conformity while reducing treatment delivery time compared to ssIMRT.

Multimodal radiotherapy dose prediction using a multi-task deep learning model

BACKGROUND

In radiation therapy (RT), accelerated partial breast irradiation (APBI) has emerged as an increasingly preferred treatment modality over conventional whole breast irradiation due to its targeted dose delivery and shorter course of treatment. APBI can be delivered through various modalities including Cobalt-60-based systems and linear accelerators with C-arm, O-ring, or robotic arm design. Each modality possesses distinct features, such as beam energy or the degrees of freedom in treatment planning, which influence their respective dose distributions. These modality-specific considerations emphasize the need for a quantitative approach in determining the optimal dose delivery modality on a patient-specific basis. However, manually generating treatment plans for each modality across every patient is time-consuming and clinically impractical.

PURPOSE

We aim to develop an efficient and personalized approach for determining the optimal RT modality for APBI by training predictive models using two different deep learning-based convolutional neural networks. The baseline network performs a single-task (ST), predicting dose for a single modality. Our proposed multi-task (MT) network, which is capable of leveraging shared information among different tasks, can concurrently predict dose distributions for various RT modalities. Utilizing patient-specific input data, such as a patient's computed tomography (CT) scan and treatment protocol dosimetric goals, the MT model predicts patient-specific dose distributions across all trained modalities. These dose distributions provide patients and clinicians quantitative insights, facilitating informed and personalized modality comparison prior to treatment planning.

METHODS

The dataset, comprising 28 APBI patients and their 92 treatment plans, was partitioned into training, validation, and test subsets. Eight patients were dedicated to the test subset, leaving 68 treatment plans across 20 patients to divide between the training and validation subsets. ST models were trained for each modality, and one MT model was trained to predict doses for all modalities simultaneously. Model performance was evaluated across the test dataset in terms of Mean Absolute Percent Error (MAPE). We conducted statistical analysis of model performance using the two-tailed Wilcoxon signed-rank test.

RESULTS

Training times for five ST models ranged from 255 to 430 min per modality, totaling 1925 min, while the MT model required 2384 min. MT model prediction required an average of 1.82 s per patient, compared to ST model predictions at 0.93 s per modality. The MT model yielded MAPE of 1.1033 ± 0.3627% as opposed to the collective MAPE of 1.2386 ± 0.3872% from ST models, and the differences were statistically significant (p = 0.0003, 95% confidence interval = [-0.0865, -0.0712]).

CONCLUSION

Our study highlights the potential benefits of a MT learning framework in predicting RT dose distributions across various modalities without notable compromises. This MT architecture approach offers several advantages, such as flexibility, scalability, and streamlined model management, making it an appealing solution for clinical deployment. With such a MT model, patients can make more informed treatment decisions, physicians gain more quantitative insight for pre-treatment decision-making, and clinics can better optimize resource allocation. With our proposed goal array and MT framework, we aim to expand this work to a site-agnostic dose prediction model, enhancing its generalizability and applicability.

Application of High-Z Nanoparticles to Enhance Current Radiotherapy Treatment

Radiotherapy is an essential component of the treatment regimens for many cancer patients. Despite recent technological advancements to improve dose delivery techniques, the dose escalation required to enhance tumor control is limited due to the inevitable toxicity to the surrounding healthy tissue. Therefore, the local enhancement of dosing in tumor sites can provide the necessary means to improve the treatment modality. In recent years, the emergence of nanotechnology has facilitated a unique opportunity to increase the efficacy of radiotherapy treatment. The application of high-atomic-number (Z) nanoparticles (NPs) can augment the effects of radiotherapy by increasing the sensitivity of cells to radiation. High-Z NPs can inherently act as radiosensitizers as well as serve as targeted delivery vehicles for radiosensitizing agents. In this work, the therapeutic benefits of high-Z NPs as radiosensitizers, such as their tumor-targeting capabilities and their mechanisms of sensitization, are discussed. Preclinical data supporting their application in radiotherapy treatment as well as the status of their clinical translation will be presented.

A high-resolution large-area detector for quality assurance in radiotherapy

Hadron therapy is an advanced radiation modality for treating cancer, which currently uses protons and carbon ions. Hadrons allow for a highly conformal dose distribution to the tumour, minimising the detrimental side-effects due to radiation received by healthy tissues. Treatment with hadrons requires sub-millimetre spatial resolution and high dosimetric accuracy. This paper discusses the design, fabrication and performance tests of a detector based on Gas Electron Multipliers (GEM) coupled to a matrix of thin-film transistors (TFT), with an active area of 60 × 80 mm2 and 200 ppi resolution. The experimental results show that this novel detector is able to detect low-energy (40 kVp X-rays), high-energy (6 MeV) photons used in conventional radiation therapy and protons and carbon ions of clinical energies used in hadron therapy. The GEM-TFT is a compact, fully scalable, radiation-hard detector that measures secondary electrons produced by the GEMs with sub-millimetre spatial resolution and a linear response for proton currents from 18 pA to 0.7 nA. Correcting known detector defects may aid in future studies on dose uniformity, LET dependence, and different gas mixture evaluation, improving the accuracy of QA in radiotherapy.

Hybrid Treatment Planning for Chest Wall Irradiation Utilizing Three-Dimensional Conformal Radiotherapy (3DCRT), Intensity-Modulated Radiation Therapy (IMRT), and Volumetric Modulated Arc Therapy (VMAT): A Systematic Review

Novel hybrid approaches for chest wall irradiation show promising outcomes regarding target coverage and sparing organs at risk (OARs). In this systematic review, we compared hybrid volumetric modulated arc therapy (H-VMAT) or hybrid intensity-modulated radiotherapy (H-IMRT) techniques with non-hybrid techniques, such as three-dimensional conformal radiation therapy (3DCRT), field-in-field (FIF), intensity-modulated arc therapy (IMRT), and volumetric modulated arc therapy (VMAT), for breast cancer patients with mastectomy. Our focus was the plan quality and dose distribution to the OARs. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, we performed a systematic review and quality appraisal of primary studies evaluating hybrid therapy to the chest wall and the OARs. An extensive online search of PubMed and Scopus databases was conducted using appropriate keywords. The dose to the OARs (lung, heart, and contralateral breast), planning target volume (PTV), homogeneity index (HI), and conformity index (CI) were extracted. The data were then tabulated and compared for the outcomes between modalities among the studies. Nine studies that met the search criteria were selected to evaluate the PTV coverage and dosimetric results of hybrid and non-hybrid techniques. In terms of 95% PTV coverage, among nine reviewed studies, the largest difference between the two techniques was between VMAT (47.6 Gy) and H-VMAT (48.4 Gy); for the conformity index, the largest difference was noted between 3DCRT (0.58) and H-VMAT (0.79). In both cases, differences were statistically significant (P < 0.005). Two studies showed dose homogeneity improvement within the treatment target in H-VMAT (0.15 and 0.07) compared with 3DCRT (0.41 and 0.12), with a P value of <0.001. Two studies did not report on the homogeneity index, and three others observed no statistical difference. Regarding OARs, in the comparison of H-VMAT and VMAT, the largest significant change was in the volume receiving 5 Gy (V5Gy) of the ipsilateral lung and the V10Gy of the contralateral lung. For the ipsilateral lung, V5Gy was 90.7% with VMAT versus 51.45% with H-VMAT. For the contralateral lung, V10Gy was 54.9% with VMAT versus 50.5% with H-VMAT. In six studies, the mean dose of the contralateral breast was lower in hybrid techniques than in single modalities: VMAT (4.2%, 6.0%, 1.9%, 7.1%, 4.57%) versus H-VMAT (1.4%, 3.4%, 1.8%, 3.5%, 2.34%) and IMRT (9.1%) versus H-IMRT (4.69%). Although most studies did not report on monitor units and treatment time, those that included them showed that hybrids had lower monitor units and shorter treatment times. Hybrid techniques in radiotherapy, such as combining two modalities, can indeed facilitate lower doses to OARs for patients with a high risk of toxicities. Prospective clinical studies are needed to determine the outcomes of breast cancer treated with hybrid techniques.

Treatment Complications of Head and Neck Cancers and Rehabilitation Measures: A Narrative Review

Head and neck cancers (HNCs) are malignant tumors mainly from squamous cells in the head and neck tissues. Treatment involves a multidisciplinary approach with surgery, radiotherapy, and chemotherapy. However, the long-term prognosis for patients with advanced-stage tumors is guarded, with a median survival time of approximately 24 months. HNC patients have very high rates of depression and anxiety and the highest suicide rate among all cancers due to the intense and challenging nature of the treatment, underscoring the importance of our collective efforts. Rehabilitation success depends on various factors, including tumor, patient, and treatment-related factors. Patients may require post-treatment oral rehabilitation measures, including implants, obturators, and flexible dentures. These measures are crucial, but they often need to be more utilized. Patients may face challenges in maintaining oral hygiene and managing mucositis. Additionally, it is essential to address other intricacies such as trismus, xerostomia, gustatory dysfunctions, neuropathy, speech impairments, and psychological disturbances. Unfortunately, there is little literature on post-treatment rehabilitative measures. Despite its crucial role in improving patients' quality of life, rehabilitation often receives inadequate attention compared to treatment. Our narrative review, which covers various factors that affect rehabilitation, including oral rehabilitation measures and post-treatment complications, is anticipated to deliver practical insights to professionals and inspire positive changes in their regular practice.

Developing an educational "hub": impact of a distance-learning curriculum in a multinational cohort

PURPOSE

To address a gap in radiation oncology education in low- and middle-income countries (LMICs), we sought to evaluate the effectiveness and generalizability of a refined curriculum on intensity modulated radiotherapy (IMRT) offered to existing radiation therapy (RT) clinics across Africa and Latin America (LATAM) at no cost.

METHODS

A curriculum was created based on prior needs assessments and adapted for participating medical physicists, radiation oncologists, radiation therapists, and trainees in LMICs. English-speaking and Spanish-speaking teams of volunteer educators delivered 27 hour-long sessions 1-2 times weekly for 4 months using video conferencing to African and LATAM cohorts, respectively. Pre- and post-course multiple-choice examinations were administered to LATAM participants, and pre- and post-course self-confidence (1-5 Likert-scale) and open-ended feedback were collected from all participants.

RESULTS

Twenty-five centers across Africa (13) and LATAM (12) participated, yielding a total of 332 enrolled participants (128 African, 204 LATAM). Sessions were delivered with a mean of 44 (22.5) and 85 (25.4) participants in the African and LATAM programs, respectively. Paired pre and post-course data demonstrated significant (p < 0.001) improvement in knowledge from 47.9 to 89.6% and self-confidence across four domains including foundations (+ 1.1), commissioning (+ 1.3), contouring (+ 1.7), and treatment planning (+ 1.0). Attendance was a significant predictor of change in self-confidence in "high attendance" participants only, suggesting a threshold effect. Qualitative data demonstrates that participants look forward to applying their knowledge in the clinical setting.

CONCLUSION

A specialized radiation oncology curriculum adapted for LMIC audiences was effective for both African and LATAM participants. Participant feedback suggests that the refined IMRT course empowered clinics with knowledge and confidence to help train others. This feasible "Hub and Spokes" approach in which a distance-learning course establishes a hub to be leveraged by spokes (learners) may be generalizable to others aiming to reduce global health care disparities through training efforts.

Energy-guided diffusion model for CBCT-to-CT synthesis

Cone Beam Computed Tomography (CBCT) plays a crucial role in Image-Guided Radiation Therapy (IGRT), providing essential assurance of accuracy in radiation treatment by monitoring changes in anatomical structures during the treatment process. However, CBCT images often face interference from scatter noise and artifacts, posing a significant challenge when relying solely on CBCT for precise dose calculation and accurate tissue localization. There is an urgent need to enhance the quality of CBCT images, enabling a more practical application in IGRT. This study introduces EGDiff, a novel framework based on the diffusion model, designed to address the challenges posed by scatter noise and artifacts in CBCT images. In our approach, we employ a forward diffusion process by adding Gaussian noise to CT images, followed by a reverse denoising process using ResUNet with an attention mechanism to predict noise intensity, ultimately synthesizing CBCT-to-CT images. Additionally, we design an energy-guided function to retain domain-independent features and discard domain-specific features during the denoising process, enhancing the effectiveness of CBCT-CT generation. We conduct numerous experiments on the thorax dataset and pancreas dataset. The results demonstrate that EGDiff performs better on the thoracic tumor dataset with SSIM of 0.850, MAE of 26.87 HU, PSNR of 19.83 dB, and NCC of 0.874. EGDiff outperforms SoTA CBCT-to-CT synthesis methods on the pancreas dataset with SSIM of 0.754, MAE of 32.19 HU, PSNR of 19.35 dB, and NCC of 0.846. By improving the accuracy and reliability of CBCT images, EGDiff can enhance the precision of radiation therapy, minimize radiation exposure to healthy tissues, and ultimately contribute to more effective and personalized cancer treatment strategies.

Sparing Swallowing-Related Structures Reduces Post-Radiotherapy Dysphagia in Oropharyngeal Cancer

OBJECTIVE

To identify swallowing-related structures (SRSs) predicting post-radiotherapy dysphagia in oropharyngeal carcinoma patients.

MATERIAL AND METHODS

Between September 2020 and October 2022, oropharyngeal cancer patients who had completed radiotherapy at least one year before without recurrence or residuals were selected. They underwent flexible endoscopic evaluation of swallowing (FEES) assessments and dysphagia grading. The mean radiation doses delivered to their SRSs were recalculated. The correlation between radiation doses to each SRS and FEES scores was analysed.

RESULTS

Twenty-nine participants, aged 51-73 years, were enrolled. Six patients had received two-dimensional radiotherapy, eight had undergone three-dimensional conformal radiotherapy, and fifteen had received intensity-modulated radiation therapy. Radiation doses to the inferior pharyngeal constrictor, cricopharyngeus and glottic larynx significantly predicted dysphagia for both semisolids (p = 0.023, 0.030 and 0.001) and liquid diets (p = 0.021, 0.013 and 0.002). The esophageal inlet significantly predicted swallowing outcomes for only the liquid diet (p = 0.007).

CONCLUSIONS

This study supports that SRS-sparing during radiotherapy for oropharyngeal cancers improves swallowing outcomes.

Brain diffusion MRI biomarkers after oncology treatments

In addition to providing a measurement of the tumor's size and dimensions, magnetic resonance imaging (MRI) provides excellent noninvasive radiographic detection of tumor location. The MRI technique is an important modality that has been shown to be useful in the prognosis, diagnosis, treatment planning, and evaluation of response and recurrence in solid cancers. Diffusion-weighted imaging (DWI) is an imaging technique that quantifies water mobility. This imaging approach is good for identifying sub-voxel microstructure of tissues, correlates with tumor cellularity, and has been proven to be valuable in the early assessment of cytotoxic treatment for a variety of malignancies. Diffusion tensor imaging (DTI) is an MRI method that assesses the preferred amount of water transport inside tissues. This enables precise measurements of water diffusion, which changes according to the direction of white matter fibers, their density, and myelination. This measurement corresponds to some related variables: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and others. DTI biomarkers can detect subtle changes in white matter microstructure and integrity following radiation therapy (RT) or chemoradiotherapy, which may have implications for cognitive function and quality of life. In our study, these indices were evaluated after brain chemoradiotherapy.

Approaches for Stereotactic Radiosurgery (SRS)/Stereotactic Radiotherapy (SRT) in brain metastases using different radiotherapy modalities (Feasibility study)

BACKGROUND

SRS and SRT are precise treatments for brain metastases, delivering high doses while minimizing doses to nearby organs. Modern linear accelerators enable the precise delivery of SRS/SRT using different modalities like three-dimensional conformal radiotherapy (3DCRT), intensity-modulated radiotherapy (IMRT), and Rapid Arc (RA).

OBJECTIVE

This study aims to compare dosimetric differences and evaluate the effectiveness of 3DCRT, IMRT, and Rapid Arc techniques in SRS/SRT for brain metastases.

METHODS

10 patients with brain metastases, 3 patients assigned for SRT, and 7 patients for SRS. For each patient, 3 treatment plans were generated using the Eclipse treatment planning system using different treatment modalities.

RESULTS

No statistically significant differences were observed among the three techniques in the homogeneity index (HI), maximum D2%, and minimum D98% doses for the target, with a p > 0.05. The RA demonstrated a better conformity index of 1.14±0.25 than both IMRT 1.21±0.26 and 3DCRT 1.37±0.31. 3DCRT and IMRT had lower Gradient Index values compared to RA, suggesting that they achieved a better dose gradient than RA. The mean treatment time decreased by 26.2% and 10.3% for 3DCRT and RA, respectively, compared to IMRT. In organs at risk, 3DCRT had lower maximum doses than IMRT and RA, but some differences were not statistically significant. However, in the brain stem and brain tissues, RA exhibited lower maximum doses compared to IMRT and 3DCRT. Additionally, RA and IMRT had lower V15Gy, V12Gy, and V9Gy values compared to 3DCRT.

CONCLUSION

While 3D-CRT delivered lower doses to organs at risk, RA and IMRT provided better conformity and target coverage. RA effectively controlled the maximum dose and irradiated volume of normal brain tissue. Overall, these findings indicate that 3DCRT, RA, and IMRT are suitable for treating brain metastases in SRS/SRT due to their improved dose conformity and target coverage while minimizing dose to healthy tissues.

Particle Swarm Optimisation Applied to the Direct Aperture Optimisation Problem in Radiation Therapy

Intensity modulated radiation therapy (IMRT) is one of the most used techniques for cancer treatment. Using a linear accelerator, it delivers radiation directly at the cancerogenic cells in the tumour, reducing the impact of the radiation on the organs surrounding the tumour. The complexity of the IMRT problem forces researchers to subdivide it into three sub-problems that are addressed sequentially. Using this sequential approach, we first need to find a beam angle configuration that will be the set of irradiation points (beam angles) over which the tumour radiation is delivered. This first problem is called the Beam Angle Optimisation (BAO) problem. Then, we must optimise the radiation intensity delivered from each angle to the tumour. This second problem is called the Fluence Map Optimisation (FMO) problem. Finally, we need to generate a set of apertures for each beam angle, making the intensities computed in the previous step deliverable. This third problem is called the Sequencing problem. Solving these three sub-problems sequentially allows clinicians to obtain a treatment plan that can be delivered from a physical point of view. However, the obtained treatment plans generally have too many apertures, resulting in long delivery times. One strategy to avoid this problem is the Direct Aperture Optimisation (DAO) problem. In the DAO problem, the idea is to merge the FMO and the Sequencing problem. Hence, optimising the radiation's intensities considers the physical constraints of the delivery process. The DAO problem is usually modelled as a Mixed-Integer optimisation problem and aims to determine the aperture shapes and their corresponding radiation intensities, considering the physical constraints imposed by the Multi-Leaf Collimator device. In solving the DAO problem, generating clinically acceptable treatments without additional sequencing steps to deliver to the patients is possible. In this work, we propose to solve the DAO problem using the well-known Particle Swarm Optimisation (PSO) algorithm. Our approach integrates the use of mathematical programming to optimise the intensities and utilizes PSO to optimise the aperture shapes. Additionally, we introduce a reparation heuristic to enhance aperture shapes with minimal impact on the treatment plan. We apply our proposed algorithm to prostate cancer cases and compare our results with those obtained in the sequential approach. Results show that the PSO obtains competitive results compared to the sequential approach, receiving less radiation time (beam on time) and using the available apertures with major efficiency.

Nanoparticle-mediated cancer cell therapy: basic science to clinical applications

Every sixth person in the world dies due to cancer, making it the second leading severe cause of death after cardiovascular diseases. According to WHO, cancer claimed nearly 10 million deaths in 2020. The most common types of cancers reported have been breast (lung, colon and rectum, prostate cases), skin (non-melanoma) and stomach. In addition to surgery, the most widely used traditional types of anti-cancer treatment are radio- and chemotherapy. However, these do not distinguish between normal and malignant cells. Additional treatment methods have evolved over time for early detection and targeted therapy of cancer. However, each method has its limitations and the associated treatment costs are quite high with adverse effects on the quality of life of patients. Use of individual atoms or a cluster of atoms (nanoparticles) can cause a paradigm shift by virtue of providing point of sight sensing and diagnosis of cancer. Nanoparticles (1-100 nm in size) are 1000 times smaller in size than the human cell and endowed with safer relocation capability to attack mechanically and chemically at a precise location which is one avenue that can be used to destroy cancer cells precisely. This review summarises the extant understanding and the work done in this area to pave the way for physicians to accelerate the use of hybrid mode of treatments by leveraging the use of various nanoparticles.

Machine Learning & Molecular Radiation Tumor Biomarkers

Developing radiation tumor biomarkers that can guide personalized radiotherapy clinical decision making is a critical goal in the effort towards precision cancer medicine. High-throughput molecular assays paired with modern computational techniques have the potential to identify individual tumor-specific signatures and create tools that can help understand heterogenous patient outcomes in response to radiotherapy, allowing clinicians to fully benefit from the technological advances in molecular profiling and computational biology including machine learning. However, the increasingly complex nature of the data generated from high-throughput and "omics" assays require careful selection of analytical strategies. Furthermore, the power of modern machine learning techniques to detect subtle data patterns comes with special considerations to ensure that the results are generalizable. Herein, we review the computational framework of tumor biomarker development and describe commonly used machine learning approaches and how they are applied for radiation biomarker development using molecular data, as well as challenges and emerging research trends.

Artificial intelligence-supported applications in head and neck cancer radiotherapy treatment planning and dose optimisation

INTRODUCTION

The aim of this review is to describe how various AI-supported applications are used in head and neck cancer radiotherapy treatment planning, and the impact on dose management in regards to target volume and nearby organs at risk (OARs).

METHODS

Literature searches were conducted in databases and publisher portals Pubmed, Science Direct, CINAHL, Ovid, and ProQuest to peer reviewed studies published between 2015 and 2021.

RESULTS

Out of 464 potential ones, ten articles covering the topic were selected. The benefit of using deep learning-based methods to automatically segment OARs is that it makes the process more efficient producing clinically acceptable OAR doses. In some cases automated treatment planning systems can outperform traditional systems in dose prediction.

CONCLUSIONS

Based on the selected articles, in general AI-based systems produced time savings. Also, AI-based solutions perform at the same level or better than traditional planning systems considering auto-segmentation, treatment planning and dose prediction. However, their clinical implementation into routine standard of care should be carefully validated IMPLICATIONS TO PRACTICE: AI has a primary benefit in reducing treatment planning time and improving plan quality allowing dose reduction to the OARs thereby enhancing patients' quality of life. It has a secondary benefit of reducing radiation therapists' time spent annotating thereby saving their time for e.g. patient encounters.

Treatment of oropharyngeal squamous cell carcinoma: Is swallowing quality better after TORS or RT?

BACKGROUND AND PURPOSE

To answer an important question regarding the long-term morbidity of two oncological equivalent treatment for oropharyngeal squamous cell carcinoma (OPSCC), namely a comparison of swallowing function results between patients treated with trans-oral robotic surgery (TORS) versus patients treated with radiotherapy (RT).

MATERIALS AND METHODS

Studies included patients with OPSCC treated with TORS or RT. Articles reporting complete data on MD Anderson Dysphagia Inventory (MDADI) and comparing the two treatments (TORS vs RT) were included in the meta-analysis. Swallowing assessed with MDADI was the primary outcome, the evaluation with instrumental methods was the secondary aim.

RESULTS

Included studies provided a total of 196 OPSCC primarily treated with TORS vs 283 OPSCC primarily treated with RT. The mean difference in MDADI score at the longest follow-up was not significantly different between TORS and RT group (mean difference [MD] -0.52; 95% CI -4.53-3.48; p = 0.80). After treatment, mean composite MDADI scores demonstrated a slight impairment in both groups without reaching a statistical difference compared to the baseline status. DIGEST score and Yale score showed a significantly worse function in both treatment groups at 12-month follow-up compared to baseline status.

CONCLUSION

The meta-analysis demonstrates that up-front TORS (+- adjuvant therapy) and up-front RT (+- CT) appear to be equivalent treatments in functional outcomes in T1-T2, N0-2 OPSCC, however, both treatments cause impaired swallowing ability. Clinicians should have a holistic approach and work with patients to develop an individualized nutrition plan and swallowing rehabilitation protocol from diagnosis to post-treatment surveillance.

Cognitive and neuroimaging outcomes in individuals with benign and low-grade brain tumours receiving radiotherapy: a protocol for a prospective cohort study

INTRODUCTION

Radiation-induced cognitive decline (RICD) occurs in 50%-90% of adult patients 6 months post-treatment. In patients with low-grade and benign tumours with long expected survival, this is of paramount importance. Despite advances in radiation therapy (RT) treatment delivery, better understanding of structures important for RICD is necessary to improve cognitive outcomes. We hypothesise that RT may affect network topology and microstructural integrity on MRI prior to any gross anatomical or apparent cognitive changes. In this longitudinal cohort study, we aim to determine the effects of RT on brain structural and functional integrity and cognition.

METHODS AND ANALYSIS

This study will enroll patients with benign and low-grade brain tumours receiving partial brain radiotherapy. Patients will receive either hypofractionated (>2 Gy/fraction) or conventionally fractionated (1.8-2 Gy/fraction) RT. All participants will be followed for 12 months, with MRIs conducted pre-RT and 6-month and 12 month post-RT, along with a battery of neurocognitive tests and questionnaires. The study was initiated in late 2018 and will continue enrolling through 2024 with final follow-ups completing in 2025. The neurocognitive battery assesses visual and verbal memory, attention, executive function, processing speed and emotional cognition. MRI protocols incorporate diffusion tensor imaging and resting state fMRI to assess structural connectivity and functional connectivity, respectively. We will estimate the association between radiation dose, imaging metrics and cognitive outcomes.

ETHICS AND DISSEMINATION

This study has been approved by the Research Subjects Review Board at the University of Rochester (STUDY00001512: Cognitive changes in patients receiving partial brain radiation). All results will be published in peer-reviewed journals and at scientific conferences.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov NCT04390906.

Comprehensive clinical evaluation of TomoEQA for patient-specific pre-treatment quality assurance in helical tomotherapy

Background

Based on a previous study on the feasibility of TomoEQA, an exit detector-based patient-specific pre-treatment quality assurance (QA) method for helical tomotherapy, an in-depth clinical evaluation was conducted.

Methods

Data of one hundred patients were analyzed to evaluate the clinical usefulness of TomoEQA for patient-specific pre-treatment QA in comparison with the conventional phantom-based method. Additional investigations were also performed under unusual measurement conditions to validate the off-axis region. In addition to the clinical evaluation of TomoEQA, a statistical analysis was conducted to determine the plan parameters that affect the pass/failure results of pre-treatment QA.

Results

The average and standard deviations of the gamma passing rate and point dose error for TomoEQA were comparable to those of the conventional QA method. For TomoEQA, the average values of the gamma passing rate and point dose error were 96.32% (standard deviation (1 sigma) = 3.94; 95% confidence interval (CI), 95.55 to 97.09) and − 1.12% (standard deviation (1 sigma) = 1.04; CI, − 1.32 to − 0.92), respectively. For the conventional QA method, the average values of the gamma passing rate and point dose error were 95.95% (standard deviation (1 sigma) = 4.35; 95% confidence interval (CI), 95.10 to 96.80) and − 1.20% (standard deviation (1 sigma) = 1.61; CI, − 1.52 to − 0.88), respectively. Further experiments on the off-axis region demonstrated that TomoEQA can provide accurate results for 3D dose analysis, which is inherently difficult in the conventional QA method. Through a statistical analysis based on the results of TomoEQA, it was validated that the total fraction (Total Fx), monitor units, beam-on-time, leaf-of-time below 100 ms, and planning target volume diameter were statistically significant for the pass/failure of the pre-treatment QA results.

Conclusions

TomoEQA is a clinically beneficial alternative to the conventional phantom-based QA method.

Volumetric modulated arc therapy (VMAT): a review of clinical outcomes—what is the clinical evidence for the most effective implementation?

Modern conformal radiation therapy using techniques such as modulation, image guidance and motion management have changed the face of radiotherapy today offering superior conformity, efficiency, and reproducibility to clinics worldwide. This review assesses the impact of these advanced radiotherapy techniques on patient toxicity and survival rates reported from January 2017 to September 2020. The main aims are to establish if dosimetric and efficiency gains correlate with improved survival and reduced toxicities and to answer the question ‘What is the clinical evidence for the most effective implementation of VMAT?’. Compared with 3DCRT, improvements have been reported with VMAT in prostate, locally advanced cervical carcinoma and various head and neck applications, leading to the shift in technology to VMAT. Other sites such as thoracic neoplasms and nasopharyngeal carcinomas have observed some improvement with VMAT although not in line with improved dosimetric measures, and the burden of toxicity and the incidence of cancer related deaths remain high, signaling the need to further mitigate toxicity and increase survival. As technological advancement continues, large randomised long-term clinical trials are required to determine the way-forward and offer site-specific recommendations. These studies are usually expensive and time consuming, therefore utilising pooled real-world data in a prospective nature can be an alternative solution to comprehensively assess the efficacy of modern radiotherapy techniques.

Accurate Signal Conditioning for Pulsed-Current Synchronous Measurements

This paper describes a compact electronic system employing a synchronous demodulation measurement method for the acquisition of pulsed-current signals. The fabricated prototype shows superior performance in terms of signal-to-noise ratio in comparison to conventional instrumentation performing free-running measurements, especially when extremely narrow pulses are concerned. It shows a reading error around 0.1% independently of the signal duty cycle (D) in the investigated D = 10−4−10−3 range. Conversely, high-precision electrometers display reading errors as high as 30% for a D = 10−4, which reduces to less than 1% only for D > 3 × 10−3. Field tests demonstrate that the developed front-end/readout electronics is particularly effective when coupled to dosimeters irradiated with the X-rays sourced by a medical linear accelerator. Therefore, it may surely be exploited for the real-time monitoring of the dosimeter output current, as required in modern radiotherapy techniques employing ultra-narrow pulses of high-energy photons or nuclear particles.

A Review of PRESAGE Radiochromic Polymer and the Compositions for Application in Radiotherapy Dosimetry

Recent advances in radiotherapy technology and techniques have allowed a highly conformal radiation to be delivered to the tumour target inside the body for cancer treatment. A three-dimensional (3D) dosimetry system is required to verify the accuracy of the complex treatment delivery. A 3D dosimeter based on the radiochromic response of a polymer towards ionising radiation has been introduced as the PRESAGE dosimeter. The polyurethane dosimeter matrix is combined with a leuco-dye and a free radical initiator, whose colour changes in proportion to the radiation dose. In the previous decade, PRESAGE gained improvement and enhancement as a 3D dosimeter. Notably, PRESAGE overcomes the limitations of its predecessors, the Fricke gel and the polymer gel dosimeters, which are challenging to fabricate and read out, sensitive to oxygen, and sensitive to diffusion. This article aims to review the characteristics of the radiochromic dosimeter and its clinical applications. The formulation of PRESAGE shows a delicate balance between the number of radical initiators, metal compounds, and catalysts to achieve stability, optimal sensitivity, and water equivalency. The applications of PRESAGE in advanced radiotherapy treatment verifications are also discussed.

Response Evaluation Following Radiation Therapy With 18F-FDG PET/CT: Common Variants of Radiation-Induced Changes and Potential Pitfalls

Radiation therapy (RT) is one of the cornerstones in cancer treatment and approximately half of all patients will receive some form of RT during the course of their cancer management. Response evaluation after RT and follow-up imaging with ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) can be complicated by RT-induced acute, chronic or consequential effects. There is a general consensus that ¹⁸F-FDG PET/CT for response evaluation should be delayed for 12 weeks after completing RT to minimize the risk of false-positive findings. Radiation-induced late side effects in normal tissue can take years to develop and eventually cause symptoms that on imaging can potentially mimic recurrent disease. Imaging findings in radiation induced injuries depend on the normal tissue included in the irradiated volume and the radiation therapy regime including the total dose delivered, dose per fraction and treatment schedule. The intent for radiation therapy should be taken in consideration when evaluating the response on imaging, that is palliative vs curative or neoadjuvant vs adjuvant RT. Imaging findings can further be distorted by altered anatomy and sequelae following surgery within the radiation field. An awareness of common PET/CT-induced changes/injuries is essential when interpreting ¹⁸F-FDG PET/CT as well as obtaining a complete medical history, as patients are occasionally scanned for an unrelated cause to previously RT treated malignancy. In addition, secondary malignancies due to carcinogenic effects of radiation exposure in long-term cancer survivors should not be overlooked. ¹⁸F-FDG PET/CT can be very useful in response evaluation and follow-up in patients treated with RT, however, variants and pitfalls are common and it is important to remember that radiation-induced injury is often a diagnosis of exclusion.

The development of a deep reinforcement learning network for dose-volume-constrained treatment planning in prostate cancer intensity modulated radiotherapy

Although commercial treatment planning systems (TPSs) can automatically solve the optimization problem for treatment planning, human planners need to define and adjust the planning objectives/constraints to obtain clinically acceptable plans. Such a process is labor-intensive and time-consuming. In this work, we show an end-to-end study to train a deep reinforcement learning (DRL) based virtual treatment planner (VTP) that can behave like a human to operate a dose-volume constrained treatment plan optimization engine following the parameters used in Eclipse TPS for high-quality treatment planning. We considered the prostate cancer IMRT treatment plan as the testbed. The VTP took the dose-volume histogram (DVH) of a plan as input and predicted the optimal strategy for constraint adjustment to improve the plan quality. The training of VTP followed the state-of-the-art Q-learning framework. Experience replay was implemented with epsilon-greedy search to explore the impacts of taking different actions on a large number of automatically generated plans, from which an optimal policy can be learned. Since a major computational cost in training was to solve the plan optimization problem repeatedly, we implemented a graphical processing unit (GPU)-based technique to improve the efficiency by 2-fold. Upon the completion of training, the established VTP was deployed to plan for an independent set of 50 testing patient cases. Connecting the established VTP with the Eclipse workstation via the application programming interface, we tested the performance the VTP in operating Eclipse TPS for automatic treatment planning with another two independent patient cases. Like a human planner, VTP kept adjusting the planning objectives/constraints to improve plan quality until the plan was acceptable or the maximum number of adjustment steps was reached under both scenarios. The generated plans were evaluated using the ProKnow scoring system. The mean plan score (± standard deviation) of the 50 testing cases were improved from 6.18 ± 1.75 to 8.14 ± 1.27 by the VTP, with 9 being the maximal score. As for the two cases under Eclipse dose optimization, the plan scores were improved from 8 to 8.4 and 8.7 respectively by the VTP. These results indicated that the proposed DRL-based VTP was able to operate the in-house dose-volume constrained TPS and Eclipse TPS to automatically generate high-quality treatment plans for prostate cancer IMRT.

Dosimetric sensitivity of leaf width on volumetric modulated arc therapy plan quality: an objective approach

Background

Several authors investigated a dosimetric impact of leaf width on radiotherapy plan quality subjectively, and concluded that thinner leaf-width multileaf collimators (MLC) are beneficial because of their better coverage of clinically relevant structures. Study aimed to investigate the dosimetric effect of MLC leaf width on volumetric modulated arc therapy plan quality by objective approach.

Materials and methods

Twelve of each prostate and head-and-neck patients were planned for volumetric modulated arc therapy (VMAT) treatments for MLC leaf widths of 4 mm and 10 mm. Three different VMAT schemes single-arc, dual-arc and two combined independent single-arcs were optimized. Dose volume histogram and Isodose distribution were used for quantitative and qualitative comparison of the treatment plan, respectively. Dose-volume-indices of the planning target volume, organs at risk and number of delivered monitor units were compared. The 4 mm leaf width being reference over 10 mm and results were noted as statistically significant if p ≤ 0.05 using student t-test.

Results

All VMAT schemes for both tumor sites showed a gain in target coverage, similar organs at risk doses and higher monitor units to be delivered, when changing leaf width from 10 mm to 4 mm. The p-values were significant for majority of head-and-neck dose indices.

Conclusion

The thinner-leaf MLCs, owing to their better spatial resolution, result in an overall gain for target coverage, while maintaining permissible doses to the organs at risk.

Current Advances in the Management of Adult Craniopharyngiomas

Craniopharyngiomas (CPs) are slow growing, histologically benign intracranial tumors located in the sellar–suprasellar region. Although known to have low mortality, their location and relationship to the adjacent neural structures results in patients having significant neurologic, endocrine, and visual comorbidities. The invasive nature of this tumor makes complete resection a challenge and contributes to its recurrence. Additionally, these tumors are bimodally distributed, being treated with surgery, and are followed by other adjuncts, such as focused radiation therapy, e.g., Gamma knife. Advances in surgical techniques, imaging tools, and instrumentations have resulted in the evolution of surgery using endoscopic techniques, with residual components being treated by radiotherapy to target the residual tumor. Advances in molecular biology have elucidated the main pathways involved in tumor development and recurrence, but presently, no other treatments are offered to patients, besides surgery, radiation, and endocrine management, as the disease and tumor evolve. We review the contemporary management of these tumors, from the evolution of surgical treatments, utilizing standard open microscopic approaches to the more recent endoscopic surgery, and discuss the current recommendations for care of these patients. We discuss the developments in radiation therapy, such as radiosurgery, being used as treatment strategies for craniopharyngioma, highlighting their beneficial effects on tumor resections while decreasing the rates of adverse outcomes. We also outline the recent chemotherapy modalities, which help control tumor growth, and the immune landscape on craniopharyngiomas that allow the development of novel immunotherapies.

The Role of Cardioprotection in Cancer Therapy Cardiotoxicity: JACC: CardioOncology State-of-the-Art Review

Cardiotoxicity is a relatively frequent and potentially serious side effect of traditional and targeted cancer therapies. Both general measures and specific pharmacologic cardioprotective interventions as well as imaging- and biomarker-based surveillance strategies to identify patients at high risk have been tested in randomized controlled trials to prevent or attenuate cancer therapy-related cardiotoxic effects. Although meta-analyses including early trials suggest an overall beneficial effect, there is substantial heterogeneity in results. Recent randomized controlled trials of neurohormonal inhibitors in patients receiving anthracyclines and/or human epidermal growth factor receptor 2-targeted therapies have shown a lower rate of cancer therapy-related cardiac dysfunction than previously reported and a modest or no sustained effect of the interventions. Data on preventive cardioprotective strategies for novel cancer drugs are lacking. Larger, prospective multicenter randomized clinical trials testing traditional and novel interventions are required to more accurately define the benefit of different cardioprotective strategies and to refine risk prediction and identify patients who are likely to benefit.

Utilizing pre-determined beam orientation information in dose prediction by 3D fully-connected network for intensity modulated radiotherapy

Background

Although the effect of pre-determined beam orientation on dose distribution of intensity modulated radiotherapy (IMRT) has been well-documented, its impacts on dose prediction are less investigated. In this study, the direction map of beam orientation was incorporated into our proposed deep-learning network and utilized in dose prediction of IMRT plans consisting of multiple static fields.

Methods

The direction map was used to characterize the radiation path through region of interest along a beam orientation. Besides, the distance map was used to characterize the spatial distribution between organs at risk (OARs) and planning target volume (PTV). The input of prediction model consisted of CT image, mask image (for PTV and OARs), distance map, and direction map. The output of prediction model was the estimated dose distribution in three dimensions. A 3D fully-connected network composed of a down-sampling encoder and an up-sampling pyramid decoder was trained based on the calculated 3D dose distributions obtained from a treatment planning system. The voxel-level mean absolute error (MAE), dosimetric metrics, and dose-volume histogram were employed to assess the quality of the estimated dose distribution. Performance of the prediction model was evaluated in two aspects. First, the effectiveness of the new features, direction map, distance maps, and pyramid decoder on prediction accuracy of model were assessed. Second, the proposed model was compared with the other three published prediction models, 3D UNet, ResNet-anti-ResNet, U-ResNet-D for inter-model evaluation.

Results

The improvement of prediction accuracy was 0.38 with the input of direction map and 0.43 with the input of distance map. Our proposed model achieved the least MAE (3.97±1.42) compared with the other three models: (5.37±1.51) for ResNet-anti-ResNet, (4.45±1.52) for U-ResNet-D, and (4.53±1.72) for Unet-3D.

Conclusions

The preliminary result demonstrated that the prediction accuracy of the proposed model was higher than those of the other three state-of-the-art prediction models. The introduction of direction maps, distance map, and pyramid decoder can effectively improve the performance of the current deep-learning network-based prediction models.

Prospective superficial EPR in-vivo dosimetry study during hypofractionated radiotherapy of breast cancer patients treated with helical tomotherapy

BACKGROUND

In-vivo dosimetry (IVD) is a patient specific measure of quality control and safety during radiotherapy. With regard to current reporting thresholds for significant occurrences in radiotherapy defined by German regulatory authorities, the present study examines the clinical feasibility of superficial electron paramagnetic resonance (EPR) IVD of cumulative total doses applied to breast cancer patients treated with helical intensity-modulated radiotherapy (tomotherapy).

METHODS

In total, 10 female patients with left- or right-sided breast cancer were enrolled in this prospective IVD study. Each patient received a hypofractionated whole breast irradiation. A total median dose of 42.4 Gy in 16 fractions (5 fractions per week) was prescribed to the planning target volume. The treatments were completely delivered using helical tomotherapy and daily image guidance via megavoltage CT (MVCT). For each patient, three EPR dosimeters were prepared and placed at distinct locations on the patient's skin during the delivery of all fractions. Two dosimeters were placed next to the ipsilateral and contralateral mammilla and one dosimeter was placed ventrally to the thyroid (out-of-primary-beam). The total doses delivered to the dosimeters were readout after all fractions had been administered. The measured total dose values were compared to the planned dose values derived from the treatment planning system (TPS). Daily positional variations (displacement vectors) of the ipsilateral mammilla and of the respective dosimeter were analyzed with respect to the planned positions using the daily registered MVCT image.

RESULTS

Averaged over all patients, the mean absolute dose differences between measured and planned total dose values (± standard deviation (SD)) were: 0.49 ± 0.85 Gy for the ipsilateral dosimeter, 0.17 ± 0.49 Gy for the contralateral dosimeter and -0.12 ± 0.30 Gy for the thyroid dosimeter. The mean lengths of the ipsilateral displacement vectors (± SD) averaged over all patients and fractions were: 10 ± 7 mm for the dosimeter and 8 ± 4 mm for the mammilla.

CONCLUSION

Superficial EPR IVD is suitable as additional safeguard for dose delivery during helical tomotherapy of breast cancer. Despite positional uncertainties in clinical routine, the observed dose deviations at the ipsilateral breast were on average small compared to national reporting thresholds for total dose deviations (i.e. 10%/4 Gy). EPR IVD may allow for the detection of critical dose errors during whole breast irradiations.

Comparison of three-dimensional patient-specific dosimetry systems with delivery errors: Toward a new synchronous measurement method

PURPOSE

This study proposed a synchronous measurement method for patient-specific dosimetry using two three-dimensional dose verification systems with delivery errors.

METHODS

Twenty hypofractionated radiotherapy treatment plans for patients with lung cancer were retrospectively reviewed. Monitor unit (MU) changes, leaf in-position errors, and angles of deviation of the collimator were intentionally introduced to investigate the detection sensitivity of the EDose + EPID (EE) and Dolphin + Compass (DC) systems.

RESULTS

Both systems accurately detected the MU modifications and had a similar ability to detect leaf in-position errors. The detection of multi-leaf collimator (MLC) errors was difficult for the whole body using different gamma criteria. When the introduced MLC error was 1.0 mm, the numbers of errors detected in the clinical target volume (CTV) by the EE system were 20, 20, and 20 and the numbers of errors detected by the DC system were 18, 19, and 20, at 3%/2 mm, 2%/2 mm, and 1%/1 mm, respectively. The average dose deviation of all DVH parameters exceeded 3%. The gamma and DVH evaluation results remained unchanged for the DC system when different collimator angle errors were introduced. The number of errors detected by the EE system was <11 for each anatomical structure for all gamma criteria. The mean dose deviation of the CTV was not distinguished.

CONCLUSIONS

This synchronous measurement approach can effectively eliminate the influence of random errors during treatment. The EE and DC systems reconstruct the three-dimensional dose distribution accurately and are convenient and reliable for dose verification.

External Validation of a Nomogram to Predict Survival and Benefit of Concurrent Chemoradiation for Stage II Nasopharyngeal Carcinoma

Simple Summary

The optimal treatment strategy (concurrent chemoradiation (CCRT) vs. radiotherapy alone) for stage II nasopharyngeal carcinoma (NPC) in the intensity-modulated radiotherapy (IMRT) era is controversial across guidelines. A nomogram by Sun et al. was published to predict the overall survival (OS) benefit of CCRT based on a patient’s clinical parameters. Using the cohort from the Hong Kong NPC1301 study, we evaluated the external validity of the nomogram and the associations between the proposed clinical factors and OS among stage II NPC patients. Use of CCRT was an insignificant predictor for OS. The nomogram lacked the predictive accuracy and should be interpreted with caution.

Abstract

A nomogram was recently published by Sun et al. to predict overall survival (OS) and the additional benefit of concurrent chemoradiation (CCRT) vs. radiotherapy (RT) alone, in stage II NPC treated with conventional RT. We aimed to assess the predictors of OS and to externally validate the nomogram in the IMRT era. We analyzed stage II NPC patients treated with definitive RT alone or CCRT between 2001 and 2011 under the territory-wide Hong Kong NPC Study Group 1301 study. Clinical parameters were studied using the Cox proportional hazards model to estimate OS. The nomogram by Sun et al. was applied with 1000 times bootstrap resampling to calculate the concordance index, and we compared the nomogram predicted and observed 5-year OS. There were 482 patients included. The 5-year OS was 89.0%. In the multivariable analysis, an age > 45 years was the only significant predictor of OS (HR, 1.98; 95%CI, 1.15–3.44). Other clinical parameters were insignificant, including the use of CCRT (HR, 0.99; 95%CI, 0.62–1.58). The nomogram yielded a concordance index of 0.55 (95% CI, 0.49–0.62) which lacked clinically meaningful discriminative power. The nomogram proposed by Sun et al. should be interpreted with caution when applied to stage II NPC patients in the IMRT era. The benefit of CCRT remained controversial.

Outcomes of primary radiotherapy with or without chemotherapy for advanced oral cavity squamous cell carcinoma: Systematic review

BACKGROUND

Surgery with adjuvant radiotherapy is the accepted standard for treatment of advanced oral cavity squamous cell carcinoma (OCSCC); however, alternative evidence suggests that definitive (chemo)radiotherapy may have similar outcomes.

METHODS

Systematic review was performed to assess the therapeutic value of radiotherapy or chemoradiotherapy as a primary modality for treating OCSCC. Meta-analysis of outcomes was performed between articles comparing radiotherapy and primary surgical treatment.

RESULTS

Meta-analysis showed less favorable results of radiotherapy compared to surgery: overall survival at 3-years (odds ratio [OR] = 0.51; 95% confidence interval [CI] = 0.34-0.77) and 5-years (OR = 0.42; 95% CI = 0.29-0.60); disease-specific survival at 3-years (OR = 0.55; 95% CI = 0.32-0.96) and 5-years (OR = 0.55; 95% CI = 0.32-0.96). Odds of feeding tube dependency were higher in primary radiotherapy group (OR = 2.67; 95% CI = 1.27-5.64).

CONCLUSIONS

Results of this study support the current perspective favoring primary surgical treatment for OCSCC in the absence of surgical contraindications.

Radiotherapy in the Era of Immunotherapy With a Focus on Non-Small-Cell Lung Cancer: Time to Revisit Ancient Dogmas?

Radiation-induced immune effects have been extensively deciphered over the last few years, leading to the concept of the dual immune effect of radiotherapy with both immunostimulatory and immunosuppressive effects. This explains why radiotherapy alone is not able to drive a strong anti-tumor immune response in most cases, hence underlining the rationale for combining both radiotherapy and immunotherapy. This association has generated considerable interest and hundreds of trials are currently ongoing to assess such an association in oncology. However, while some trials have provided unprecedented results or shown much promise, many hopes have been dashed. Questions remain, therefore, as to how to optimize the combination of these treatment modalities. This narrative review aims at revisiting the old, well-established concepts of radiotherapy relating to dose, fractionation, target volumes and organs at risk in the era of immunotherapy. We then propose potential innovative approaches to be further assessed when considering a radio-immunotherapy association, especially in the field of non-small-cell lung cancer (NSCLC). We finally propose a framework to optimize the association, with pragmatic approaches depending on the stage of the disease.

TriB-RT: Simultaneous optimization of photon, electron and proton beams

PURPOSE

To develop a novel treatment planning process (TPP) with simultaneous optimization of modulated photon, electron and proton beams for improved treatment plan quality in radiotherapy.

METHODS

A framework for fluence map optimization of Monte Carlo (MC) calculated beamlet dose distributions is developed to generate treatment plans consisting of photon, electron and spot scanning proton fields. Initially, in-house intensity modulated proton therapy (IMPT) plans are compared to proton plans created by a commercial treatment planning system (TPS). A triple beam radiotherapy (TriB-RT) plan is generated for an exemplary academic case and the dose contributions of the three particle types are investigated. To investigate the dosimetric potential, a TriB-RT plan is compared to an in-house IMPT plan for two clinically motivated cases. Benefits of TriB-RT for a fixed proton beam line with a single proton field are investigated.

RESULTS

In-house optimized IMPT are of at least equal or better quality than TPS-generated proton plans, and MC-based optimization shows dosimetric advantages for inhomogeneous situations. Concerning TriB-RT, for the academic case, the resulting plan shows substantial contribution of all particle types. For the clinically motivated case, improved sparing of organs at risk close to the target volume is achieved compared to IMPT (e.g. myelon and brainstem [Formula: see text] -37%) at cost of an increased low dose bath (healthy tissue V _10% +22%). In the scenario of a fixed proton beam line, TriB-RT plans are able to compensate the loss in degrees of freedom to substantially improve plan quality compared to a single field proton plan.

CONCLUSION

A novel TPP which simultaneously optimizes photon, electron and proton beams was successfully developed. TriB-RT shows the potential for improved treatment plan quality and is especially promising for cost-effective single-room proton solutions with a fixed beamline in combination with a conventional linac delivering photon and electron fields.

Breast cancer radiotherapy: What physicians need to know in the era of the precision medicine

Breast cancer is the most common cancer in women worldwide and encompasses a broad spectrum of diseases in one with significant epidemiological, clinical, and biological heterogeneity, which determines a different natural history and prognostic profile. Although classical tumour staging (TNM) still provides valuable information, the current reality is that the clinicians must consider other biological and molecular factors that directly influence treatment decision-making. The management of breast cancer has changed radically in the last 15 years due to significant advances in our understanding of these tumours. This knowledge has brought with it a major impact regarding surgical and systemic management and has been practice-changing, but it has also created significant uncertainties regarding how best integrate the radiotherapy treatment into the therapeutic scheme. In parallel, radiotherapy itself has also experienced major advances, new radiobiological concepts have emerged, and genomic data and other patient-specific factors must now be integrated into individualised treatment approaches. In this context, "precision medicine" seeks to provide an answer to these open questions and uncertainties. The aim of the present review is to clarify the meaning of this term and to critically evaluate its role and impact on contemporary breast cancer radiotherapy.

Insights into the theranostic value of precision medicine on advanced radiotherapy to breast cancer

Breast cancer is the most common cancer in women worldwide. "Breast cancer" encompasses a broad spectrum of diseases (i.e., subtypes) with significant epidemiological, clinical, and biological heterogeneity. Each of these subtypes has a different natural history and prognostic profile. Although tumour staging (TNM classification) still provides valuable information in the overall management of breast cancer, the current reality is that clinicians must consider other biological and molecular factors that directly influence treatment decision-making, including extent of surgery, indication for chemotherapy, hormonal therapy, and even radiotherapy (and treatment volumes). The management of breast cancer has changed radically in the last 15 years due to significant advances in our understanding of these tumours. While these changes have been extremely positive in terms of surgical and systemic management, they have also created significant uncertainties concerning integration of local and locoregional radiotherapy into the therapeutic scheme. In parallel, radiotherapy itself has also experienced major advances. Beyond the evident technological advances, new radiobiological concepts have emerged, and genomic data and other patient-specific factors must now be integrated into individualized treatment approaches. In this context, "precision medicine" seeks to provide an answer to these open questions and uncertainties. Although precision medicine has been much discussed in the last five years or so, the concept remains somewhat ambiguous, and it often appear to be used as a "catch-all" term. The present review aims to clarify the meaning of this term and, more importantly, to critically evaluate the role and impact of precision medicine on breast cancer radiotherapy. Finally, we will discuss the current and future of precision medicine in radiotherapy.

3D conformal, IMRT and VMAT for the treatment of head and neck cancer: a brief literature review

Aim:

The objective of this study has been to identify monitor unit (MU) and treatment time variations, volume coverage dissimilarity among 3D conformal radiation therapy (3D-CRT), intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) treatment plans for head and neck cancer (HNC) based on literature review.

Methods:

A number of HNC cases were studied with the investigation of conformity and homogeneity index.

Results:

When high-dose modulation was required around small organs at risk (OARs), a clinically acceptable IMRT plan was achieved as VMAT usually required longer dose optimisation time. The greatest benefit of VMAT has been rapid treatment delivery allowing improved patient comfort, reduced intra-fraction motion and increased patient throughput. In some papers, 3D-CRT was shown not to meet well the requirements on parotid glands. One paper showed that cerebellum dose was lower for 3D-CRT than IMRT. However, it was found in other papers that OAR sparing with 3D-CRT was reasonable but in complex cases not enough.

Conclusions:

IMRT usually consists of several treatment fields with different directions, hundreds of beam lets with modulated intensity, an advantage over 3D-CRT, whereas VMAT has advantage over IMRT due to rotating beam utilisation. VMAT has lower total MU and treatment times than IMRT and 3D-CRT, while maintaining similar dosimetric endpoints.

Sensitivity of radio-photoluminescence glass dosimeters to accumulated doses

Background

This study investigated the effect of accumulated doses on radio-photoluminescence glass dosimeters (RPLGDs) from measurements involving mega-voltage photons.

Methods

Forty-five commercially available RPLGDs were irradiated to estimate their dose responses. Photon beams of 6, 10, and 15 MV were irradiated onto the RPLGDs inside a phantom, which were divided into five groups with different doses and energies. Groups 1 and 2 were irradiated at 1, 5, 10, 50, and 100 Gy in a sequential manner; Group 3 was irradiated 10 times with a dose of 10 Gy; and Groups 4 and 5 followed the same method as that of Group 3, but with doses of 50 Gy and 100 Gy, respectively. Each device was subjected to a measurement reading procedure each time irradiation.

Results

For the annealed Group 1, RPLGD exhibited a linearity response with variance within 5%. For the non-annealed Group 2, readings demonstrated hyperlinearity at 6 MV and 10 MV, and linearity at 15 MV. Following the 100 Gy irradiation, the readings for Group 2 were 118.7 ± 1.9%, 112.2 ± 2.7%, and 101.5 ± 2.3% at 6, 10, and 15 MV, respectively. For Groups 3, 4, and 5, the responsiveness of the RPLGDs gradually decreased as the number of repeated irradiations increased. The percentage readings for the 10th beam irradiation with respect to the readings for the primary beam irradiation were 84.6 ± 1.9%, 87.5 ± 2.4%, and 93.0 ± 3.0% at 6 MV, 10 MV, and 15 MV, respectively.

Conclusions

The non-annealed RPLGD response to dose was hyperlinear for the 6 MV and 10 MV photon beams but not for the 15 MV photon beam. Additionally, the annealed RPLGD exhibited a fading phenomenon when the measurement was repeated several times and demonstrated a relatively large fading effect at low energies than at high energies.

Volumetric modulated arc therapy: a dosimetric comparison with dynamic IMRT and step-and-shoot IMRT

Aim:

The aim of this study was to compare volumetric modulated arc therapy (VMAT) with dynamic intensity-modulated radiation therapy (dIMRT) and step-and-shoot IMRT (ssIMRT) for different treatment sites.

Materials and methods:

Twelve patients were selected for the planning comparison study. This included three head and neck, three brain, three rectal and three cervical cancer patients. Total dose of 50 Gy was given for all the plans. Plans were done for Elekta synergy with Monaco treatment planning system. All plans were generated with 6 MV photons beam. Plan evaluation was based on the ability to meet the dose volume histogram, dose homogeneity index, conformity index and radiation delivery time, and monitor unit needs to deliver the prescribed dose.

Results:

The VMAT and dIMRT plans achieved the better conformity (CI98% = 0·965 ± 0·023) and (CI98% = 0·939 ± 0·01), respectively, while ssIMRT plans were slightly inferior (CI98% = 0·901 ± 0·038). The inhomogeneity in the planning target volume (PTV) was highest with ssIMRT with HI equal to 0·097 ± 0·015 when compared to VMAT with HI equal to 0·092 ± 0·0369 and 0·095 ± 0·023 with dIMRT. The integral dose is found to be inferior with VMAT 105·31 ± 53·6 (Gy L) when compared with dIMRT 110·75 ± 52·9 (Gy L) and ssIMRT 115 38 ± 55·1(Gy L). All the techniques respected the planning objective for all organs at risk. The delivery time per fraction for VMAT was much lower than dIMRT and ssIMRT.

Findings:

Our results indicate that dIMRT and VMAT provide better sparing of normal tissue, homogeneity and conformity than ssIMRT with reduced treatment delivery time.